Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

When vulnerability remediation succeeds at enterprise scale, it’s very rarely because the vulnerability management team is finding more vulnerabilities. It’s because the program was built around the idea of turning messy findings into steady, measurable risk reduction. That’s not an easy task. It’s easier to make it a numbers game, pointing to vulnerability volumes and how many findings were addressed, rather than accurately depicting how much real risk was eliminated.

When threat actors target your vendors, they’re not just looking to exploit a system for a single attack. They’re looking for every opportunity to scale up their operations. This means seeking ways to push their compromises as far downstream into the supply chain as they can go.

‍ ‍Artificial intelligence (AI) systems and GenAI tools are no longer merely being experimented with in the market. Instead, they are being embedded into the organizational infrastructure at large, shaping how enterprises process data, automate decisions, and provide core services to customers. Unfortunately, while this integration increases efficiency, it simultaneously increases exposure to a dramatic extent.

This is why platforms like ServiceNow AI Control Tower are showing up in governance roadmaps. Control Tower helps organizations standardize how AI systems are requested, reviewed, cataloged, and managed across their lifecycle. It can bring order to chaos. But there’s a second, equally important reality: the strongest governance workflow in the world can’t govern what it can’t see.